digraph G {
0 [labelType="html" label="<br><b>TakeOrderedAndProject</b><br><br>"];
subgraph cluster1 {
isCluster="true";
label="WholeStageCodegen (1)\n \nduration: total (min, med, max (stageId: taskId))\n33 ms (9 ms, 24 ms, 24 ms (stage 59.0: task 71))";
2 [labelType="html" label="<br><b>Project</b><br><br>"];
3 [labelType="html" label="<b>Filter</b><br><br>number of output rows: 125"];
4 [labelType="html" label="<b>ColumnarToRow</b><br><br>number of output rows: 46,236<br>number of input batches: 13"];
}
5 [labelType="html" label="<b>Scan parquet spark_catalog.default.airports</b><br><br>number of files read: 2<br>scan time total (min, med, max (stageId: taskId))<br>25 ms (8 ms, 17 ms, 17 ms (stage 59.0: task 71))<br>metadata time: 0 ms<br>size of files read: 2.1 MiB<br>number of output rows: 46,236"];
2->0;
3->2;
4->3;
5->4;
}
6
TakeOrderedAndProject(limit=5, orderBy=[C_24#4803 DESC NULLS LAST], output=[C_13#4790,C_23#4791,C_15#4792,C_19#4793,C_21#4794,C_18#4795,C_25#4796,C_20#4797,C_16#4798,C_22#4799,C_12#4800,C_17#4801,C_14#4802,C_24#4803])
Project [id#4804 AS C_13#4790, type#4805 AS C_23#4791, name#4806 AS C_15#4792, (round((lat#4807 * 1000.0), 0) / 1000.0) AS C_19#4793, (round((lon#4808 * 1000.0), 0) / 1000.0) AS C_21#4794, (round((elev#4809 * 1000.0), 0) / 1000.0) AS C_18#4795, continent#4810 AS C_25#4796, country#4811 AS C_20#4797, region#4812 AS C_16#4798, city#4813 AS C_22#4799, iata#4814 AS C_12#4800, code#4815 AS C_17#4801, gps#4816 AS C_14#4802, elev#4809 AS C_24#4803]
Filter (((((isnotnull(lon#4808) AND isnotnull(lat#4807)) AND (lon#4808 <= -104.05)) AND (lon#4808 >= -111.05)) AND (lat#4807 >= 41.0)) AND (lat#4807 <= 45.0))
ColumnarToRow
WholeStageCodegen (1)
FileScan parquet spark_catalog.default.airports[id#4804,type#4805,name#4806,lat#4807,lon#4808,elev#4809,continent#4810,country#4811,region#4812,city#4813,iata#4814,code#4815,gps#4816] Batched: true, DataFilters: [isnotnull(lon#4808), isnotnull(lat#4807), (lon#4808 <= -104.05), (lon#4808 >= -111.05), (lat#480..., Format: Parquet, Location: InMemoryFileIndex(1 paths)[file:/home/acdcadmin/spark-warehouse/airports], PartitionFilters: [], PushedFilters: [IsNotNull(lon), IsNotNull(lat), LessThanOrEqual(lon,-104.05), GreaterThanOrEqual(lon,-111.05), G..., ReadSchema: struct<id:string,type:string,name:string,lat:double,lon:double,elev:double,continent:string,count...
== Physical Plan ==
TakeOrderedAndProject (5)
+- * Project (4)
+- * Filter (3)
+- * ColumnarToRow (2)
+- Scan parquet spark_catalog.default.airports (1)
(1) Scan parquet spark_catalog.default.airports
Output [13]: [id#4804, type#4805, name#4806, lat#4807, lon#4808, elev#4809, continent#4810, country#4811, region#4812, city#4813, iata#4814, code#4815, gps#4816]
Batched: true
Location: InMemoryFileIndex [file:/home/acdcadmin/spark-warehouse/airports]
PushedFilters: [IsNotNull(lon), IsNotNull(lat), LessThanOrEqual(lon,-104.05), GreaterThanOrEqual(lon,-111.05), GreaterThanOrEqual(lat,41.0), LessThanOrEqual(lat,45.0)]
ReadSchema: struct<id:string,type:string,name:string,lat:double,lon:double,elev:double,continent:string,country:string,region:string,city:string,iata:string,code:string,gps:string>
(2) ColumnarToRow [codegen id : 1]
Input [13]: [id#4804, type#4805, name#4806, lat#4807, lon#4808, elev#4809, continent#4810, country#4811, region#4812, city#4813, iata#4814, code#4815, gps#4816]
(3) Filter [codegen id : 1]
Input [13]: [id#4804, type#4805, name#4806, lat#4807, lon#4808, elev#4809, continent#4810, country#4811, region#4812, city#4813, iata#4814, code#4815, gps#4816]
Condition : (((((isnotnull(lon#4808) AND isnotnull(lat#4807)) AND (lon#4808 <= -104.05)) AND (lon#4808 >= -111.05)) AND (lat#4807 >= 41.0)) AND (lat#4807 <= 45.0))
(4) Project [codegen id : 1]
Output [14]: [id#4804 AS C_13#4790, type#4805 AS C_23#4791, name#4806 AS C_15#4792, (round((lat#4807 * 1000.0), 0) / 1000.0) AS C_19#4793, (round((lon#4808 * 1000.0), 0) / 1000.0) AS C_21#4794, (round((elev#4809 * 1000.0), 0) / 1000.0) AS C_18#4795, continent#4810 AS C_25#4796, country#4811 AS C_20#4797, region#4812 AS C_16#4798, city#4813 AS C_22#4799, iata#4814 AS C_12#4800, code#4815 AS C_17#4801, gps#4816 AS C_14#4802, elev#4809 AS C_24#4803]
Input [13]: [id#4804, type#4805, name#4806, lat#4807, lon#4808, elev#4809, continent#4810, country#4811, region#4812, city#4813, iata#4814, code#4815, gps#4816]
(5) TakeOrderedAndProject
Input [14]: [C_13#4790, C_23#4791, C_15#4792, C_19#4793, C_21#4794, C_18#4795, C_25#4796, C_20#4797, C_16#4798, C_22#4799, C_12#4800, C_17#4801, C_14#4802, C_24#4803]
Arguments: 5, [C_24#4803 DESC NULLS LAST], [C_13#4790, C_23#4791, C_15#4792, C_19#4793, C_21#4794, C_18#4795, C_25#4796, C_20#4797, C_16#4798, C_22#4799, C_12#4800, C_17#4801, C_14#4802, C_24#4803]